Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

2.7K
The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
2.7K
Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response01:15

Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response

450
Circadian rhythms are cyclic changes that are crucial in plasma drug concentrations. Various standard circadian parameters, including core body temperature, heart rate, and other cardiovascular factors, directly impact disease states and the therapeutic response to drug therapy.
The time of drug administration is an important factor to consider, as it can influence the toxic dose of a drug. For example, a study conducted by Prins et al. in 1997 examined the effects of the timing of...
450
Therapeutic Drug Monitoring: Drug Analysis Methods01:26

Therapeutic Drug Monitoring: Drug Analysis Methods

281
Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood or body tissues to tailor drug therapy effectively. This monitoring is critical for managing drugs with narrow therapeutic indices like digoxin and phenytoin, ensuring they are both safe and effective. For instance, monitoring theophylline levels in asthma patients involves precision and sensitivity to adjust doses according to individual responses to therapy, ensuring efficacy and...
281
Dosage Regimen: Multiple Oral Dosage01:25

Dosage Regimen: Multiple Oral Dosage

341
Understanding how a drug's concentration fluctuates within the body over time is crucial in pharmacokinetics, particularly with multiple oral doses. A graphical representation of multiple oral dosages provides insight into these dynamics. Typical accumulation curves of a drug's concentration in the body reveal a sawtooth pattern, indicating periodic peaks and troughs correlating with each dose administration and the drug's subsequent elimination.The plasma concentration at any time during an...
341
Pharmacokinetic–Pharmacodynamic Relationship: Problems01:24

Pharmacokinetic–Pharmacodynamic Relationship: Problems

70
The empirical approach to drug therapy optimization relies on correlating pharmacological response with administered dosage. Such an approach can be costly, time-consuming, and often yields poor correlation due to variables like formulation factors and drug elimination characteristics. A more precise approach correlates response with plasma drug concentration or the amount of drug in the body, rather than dosage. This is achieved through pharmacokinetic-pharmacodynamic (PK/PD) modeling, which...
70
Therapeutic Drug Monitoring: Affecting Factors01:29

Therapeutic Drug Monitoring: Affecting Factors

322
Therapeutic Drug Monitoring (TDM) is the clinical practice of measuring specific drug levels in a patient's blood or body tissues to manage and optimize therapy. TDM is crucial for drugs with narrow therapeutic windows, like warfarin and phenytoin, where incorrect doses can lead to treatment failure or severe side effects. This monitoring ensures the dosage administered is within a safe and effective range. The factors affecting therapeutic drug monitoring include:Patient-Specific Factors:a.
322

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Applied Practice and Possible Leverage Points for Information Technology Support for Patient Screening in Clinical Trials: Qualitative Study.

JMIR medical informatics·2020
Same author

Three-Dimensional Portable Document Format (3D PDF) in Clinical Communication and Biomedical Sciences: Systematic Review of Applications, Tools, and Protocols.

JMIR medical informatics·2018
Same author

Using Interactive 3D PDF for Exploring Complex Biomedical Data: Experiences and Solutions.

Studies in health technology and informatics·2016
Same author

User Satisfaction Evaluation of the EHR4CR Query Builder: A Multisite Patient Count Cohort System.

BioMed research international·2015
Same author

Evaluation of Automated Volumetric Cartilage Quantification for Hip Preservation Surgery.

The Journal of arthroplasty·2015
Same author

Towards a Computable Data Corpus of Temporal Correlations between Drug Administration and Lab Value Changes.

PloS one·2015

Related Experiment Video

Updated: Mar 23, 2026

A Computerized Test Battery to Study Pharmacodynamic Effects on the Central Nervous System of Cholinergic Drugs in Early Phase Drug Development
07:02

A Computerized Test Battery to Study Pharmacodynamic Effects on the Central Nervous System of Cholinergic Drugs in Early Phase Drug Development

Published on: February 11, 2019

10.3K

Dramatyping: a generic algorithm for detecting reasonable temporal correlations between drug administration and lab

Axel Newe1

  • 1Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nuremberg , Erlangen, Germany.

Peerj
|April 5, 2016
PubMed
Summary

This study introduces an algorithm to detect temporal correlations between drug intake and lab value changes, aiding in adverse drug reaction identification. The algorithm demonstrates high sensitivity and specificity for screening electronic health records.

Keywords:
Adverse drug reactionAlgorithmDramatypingObservable drug eventTemporal correlation

More Related Videos

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis
07:48

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

9.3K
Pretargeted Radioimmunotherapy Based on the Inverse Electron Demand Diels-Alder Reaction
09:44

Pretargeted Radioimmunotherapy Based on the Inverse Electron Demand Diels-Alder Reaction

Published on: January 29, 2019

10.7K

Related Experiment Videos

Last Updated: Mar 23, 2026

A Computerized Test Battery to Study Pharmacodynamic Effects on the Central Nervous System of Cholinergic Drugs in Early Phase Drug Development
07:02

A Computerized Test Battery to Study Pharmacodynamic Effects on the Central Nervous System of Cholinergic Drugs in Early Phase Drug Development

Published on: February 11, 2019

10.3K
Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis
07:48

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

9.3K
Pretargeted Radioimmunotherapy Based on the Inverse Electron Demand Diels-Alder Reaction
09:44

Pretargeted Radioimmunotherapy Based on the Inverse Electron Demand Diels-Alder Reaction

Published on: January 29, 2019

10.7K

Area of Science:

  • Pharmacovigilance
  • Clinical Informatics
  • Biostatistics

Background:

  • Assessing adverse drug reactions (ADRs) requires evaluating the temporal relationship between drug administration and observed effects.
  • Standardized criteria, like those from the World Health Organization, emphasize this temporal link for causality assessment.
  • Electronic health records (EHRs) contain vast data suitable for analyzing drug-reaction timelines.

Purpose of the Study:

  • To present and describe a novel algorithm for detecting temporal correlations between drug administration and laboratory value alterations.
  • To develop a universally applicable tool for identifying potential adverse drug reactions (ADRs) by analyzing lab value trends.
  • To provide a computational method that supports human experts in the detection of ADRs.

Main Methods:

  • Development of an algorithm designed to process normalized laboratory values.
  • Implementation of a method to analyze the temporal course of laboratory values in relation to drug administration.
  • Validation of the algorithm's performance using sensitivity and specificity metrics.

Main Results:

  • The algorithm achieved a sensitivity of 0.932 in detecting lab value changes temporally correlated with drug administration.
  • The algorithm demonstrated a specificity of 0.967 in identifying lab value courses without changes related to drug administration.
  • The algorithm is suitable for screening large datasets within electronic health records.

Conclusions:

  • The developed algorithm effectively detects temporal correlations between drug intake and laboratory value changes.
  • This tool can significantly support the identification of adverse drug reactions (ADRs) by screening EHR data.
  • The algorithm's high sensitivity and specificity make it a valuable asset for pharmacovigilance and clinical decision support.